Ha Nguyen, PhD

Assistant Professor, Instructional Technology & Learning Sciences, Utah State University

I design and research technologies to promote deeper STEM knowledge, competency, and skills for diverse learners.

My current research has dual focus on Design and Analytics. From a Design perspective, I partner with students, educators, and community organizations to ground the design of technologies (e.g., conversational agents, learning dashboards) in learners' experiences. I further apply learning analytics methods to investigate how people construct knowledge in informal and formal learning environments, in collaboration with others or with AI technologies. This Analytics strand generates insights to inform technology design, to support human-human and human-AI exchanges towards productive learning. My research has been published in leading journals in learning analytics and science education, including Computers & Education, British Journal of Education Technology, Journal of Research in Science Teaching, and Journal of Learning Analytics. I received a PhD in Education from University of California-Irvine, mentored by Drs. June Ahn, Rossella Santagata, and Mark Warschauer.

I am the Co-Principal Investigator on a National Science Foundation grant exploring the co-design of conversational agents to support science communication with high school students, informal and formal educators, STEM professionals, and community representatives (ITEST 2241596; 2023-2026). This work aims to create insights around how conversational AI agents can be positioned to represent different community perspectives and promote equity-centered science learning.

I am recruiting PhD students in the Instructional Technology & Learning Sciences program at Utah State University (See PhD Recruit for details).

Selected Publications

Journal Articles

Nguyen, H., & Parameswaran, P. (2023). Meaning making and relatedness: Exploring critical data literacies on social media. Information & Learning Sciences, 124 (5/6), 149-167. https://doi.org/10.1108/ILS-02-2023-0016

Nguyen, H., Lopez, J., Homer, B., Ali, A., & Ahn, J. (2023). Reminders, reflections, and relationships: Insights from the design of a chatbot for college advising. Information & Learning Sciences, 124(3/4), 128-146. https://doi.org/10.1108/ILS-10-2022-0116

Nguyen, H.. (2023). Role design considerations of conversational agents to facilitate discussion and systems thinking. Computers & Education, 192. https://doi.org/10.1016/j.compedu.2022.104661

Nguyen, H.. (2022). Let’s teach Kibot: Discovering discussion patterns between student groups and two conversational agent designs. British Journal of Educational Technology. http://doi.org/10.1111/bjet.13219

Campos, F., Ahn, J., Digiacomo, D., Nguyen, H., & Hays, M. (2021). Making sense of sensemaking: Understanding how K-12 teachers and coaches react to visual analytics. Journal of Learning Analytics, 8(3). https://www.learning-analytics.info/index.php/JLA/article/view/7113

Nguyen, H., Lim, K.Y., Wu, L., Fischer, C., & Warschauer, M. (2021). “We’re looking good”: Social exchange and regulation temporality in collaborative design. Learning & Instruction, 74 (2021). https://doi.org/10.1016/j.learninstruc.2021.101443 [pdf]

Ahn, J., Nguyen, H., & Campos, F. (2021). From visible to understandable: Designing for teacher agency in education data visualizations. Contemporary Issues in Technology And Teacher Education. [pdf]

Santagata, R., König, J., Scheiner, T., Nguyen, H., Adleff, A.-K., Yang, X., & Kaiser, G. (2021). Mathematics teacher learning to notice: A systematic review of studies of video-supported teacher education. ZDM - Mathematics Education. https://doi.org/10.1007/s11858-020-01216-z

Nguyen, H. & Santagata, R. (2020). Impact of computer modeling on learning and teaching systems thinking. Journal of Research in Science Teaching, 58(5), 661-688. https://doi.org/10.1002/tea.21674

Nguyen, H., Wu, L., Fischer, C., Washington, G., & Warschauer, M. (2020). Increasing success in college: Examining the impact of a project-based introductory engineering course. Journal of Engineering Education. https://doi.org/10.1002/jee.20319

Peer-Reviewed Proceedings

Nguyen, H. (2023). TikTok as learning analytics data: Framing climate change and data practices. In LAK23: 13th International Conference on Learning Analytics and Knowledge (pp. 33-43). https://doi.org/10.1145/3576050.3576055

Nguyen, H. (2022). Examining teenagers’ perceptions of conversational agents in learning settings. In IDC’22: Interaction Design & Children (pp. 374-381). https://doi.org/10.1145/3501712.3529740

Nguyen, H. (2022). Learners’ reactions to chatbot communication breakdowns: Insights into fostering learning. In The 2nd Annual Meeting of the International Society of the Learning Sciences (Online). International Society of the Learning Sciences.

Nguyen, H. & Young, W. (2022). Knowledge construction and uncertainty in real world argumentation: A text analysis approach. In The 12th International Conference on Learning Analytics and Knowledge (LAK22). (pp. 34-44).https://dl.acm.org/doi/fullHtml/10.1145/3506860.3506864

Ahn, J., Nguyen, H., Campos, F., & Young, W. (2021). Transforming everyday information into practical analytics with crowdsourced assessment tasks. In The 11th International Conference on Learning Analytics and Knowledge (LAK21) https://doi.org/10.1145/3448139.3448146

Ahn, J., Campos, F., Nguyen, H., Hays, M., & Morrison, J. (2021). Co-Designing for privacy, transparency, and trust in K-12 learning analytics. In The 11th International Conference on Learning Analytics and Knowledge (LAK21) https://doi.org/10.1145/3448139.3448145

Nguyen, H., Ahn, J., Belgrave, A., Lee, J., Cawelti, L., Kim, H.E., Prado, Y., Santagata, R., & Villavicencio, A. (2021). Establishing trustworthiness through algorithmic approaches to qualitative research. In Second International Conference on Quantitative Ethnography. Springer. https://doi.org/10.1007/978-3-030-67788-6_4 [pdf]

Nguyen, H., Ahn, J., Young, W., & Campos, F. (2020). Where's the learning in education crowdsourcing? In Proceedings of the Seventh (2020) Annual ACM Conference on Learning@ Scale. https://doi.org/10.1145/3386527.3406734

Book Chapters

Nguyen, H., Campos, F., & Ahn, J. (2021). Designing for generative uncertainty in learning dashboards. In Ifenthaler, D., & Muhittin, S. (Eds), Visualizations and dashboards for learning analytics (pp. 457-475). Springer, Cham.

Nguyen, H., Campos, F., & Ahn, J. (2021). Expanding the design space of data and action in education: What co-designing with educators reveal about current possibilities and limitations. In Bowers, A. (Ed), Data visualization, dashboards, and evidence use in schools: Data collaborative workshop perspectives of educators, researchers, and data scientists. Teachers College, Columbia University. New York, NY. https://doi.org/10.7916/d8-jj2g-e225


AISciComm: AI for Science Communication

We develop conversational agents to represent perspectives from scientists, environmental activists, and students, to promote equity-centered science communication in high school. This NSF-funded work represents a partnership with researchers at UC Irvine and community organizations in Orange County, CA.

DataScape: Developing Data Literacy in Elementary Grades

With funding from USU Research Catalyst Seed Grant, I collaborate with middle school teachers and Dr. Anna Miller from USU College of Natural Resources to develop a curriculum about data literacy and systems thinking. This work supports students to draw from personal experiences, knowledge, and assets to identify, collect, analyze, and communicate with data about recreation decision-making at different scales.

Kibot: Role Designs of Agents in Science Discussion

I designed different roles (a peer or an expert) for a conversational agent with students and informal educators. The agent provided discussion hints for high school students with different social and learning needs, to facilitate knowledge construction and understanding of environmental ecosystems.


Courses taught at Utah State University

Games & Learning. Fall 2022, 2023. Graduate Level.

Design Processes & Perspectives II. Spring 2023, 2024. Undergraduate Level.

Introduction to Learning Analytics. Spring 2024. Graduate Level.